The invention relates to a method and a device for the quality evaluation of a component produced by means of an additive manufacturing method.
Additive manufacturing methods refer to processes in which material is deposited layer by layer on the basis of 3D design data in order to build up a component in an additive manner. Accordingly, additive or generative manufacturing methods differ from conventional material-removal or primary forming methods of fabrication. Instead of milling a workpiece from a solid block, for example, additive manufacturing methods build up components layer by layer from one or more materials. Examples of additive manufacturing methods are additive laser sintering or laser melting methods, which are used to produce components for aircraft engines, for example. Such a method is already known from DE 10 2004 017 769 B4, for example. In selective laser melting, thin layers of powder of the material or materials used are applied onto a construction platform and locally melted and solidified by using one or more laser beams. Afterward, the platform is lowered and another layer of powder is applied and again locally solidified. This cycle is repeated until the finished component is obtained. The finished component can subsequently be further processed as needed or can be used immediately. In selective laser sintering, the component is produced in a similar way by laser-assisted sintering of powder-form materials.
However, for the use of components that are produced by additive laser methods and can be subjected to high loads, a process approval is required, which, in turn, requires the monitoring of diverse process parameters, such as, for example, the laser power, the nature and condition of the material powder, and the like. In this case, the individual process parameters need to be monitored at intervals in the framework of a process monitoring by using a complex method of measurement that is adapted to the case at hand. A method for monitoring the layer build-up, which is known in and of itself, is optical tomography (OT), which, for each component layer produced, affords image data that enables conclusions to be drawn about the quality of the additive manufacturing process and thus of the component produced. It would be desirable in this case to employ, in particular, an automatic evaluation of process fluctuations, which, in general, are manifested by relatively smaller intensity values in the OT image data. The quantification of the brightness values can be established on the basis of the quantity of influencing parameters, but so far not on absolute values. Even a qualitatively optimal target process is subject to different influences, such as, for instance, the component geometry, the construction platform occupancy, the position within the component, etc. and accordingly can lead to image data having changing gray-value regions, which, however, nonetheless still characterize a qualitatively good component. In particular, when image regions whose brightness values lie below a certain tolerance band are evaluated, erroneous interpretations often ensue, because, for example, image sections having darker brightness values necessarily occur at component edges on account of the transition from component to powder and these image sections are erroneously interpreted as being quality defects. Similarly, in so-called max images, which to date have been employed for quality evaluation in most applications, darker regions are formed between the scanning frequencies and likewise are then wrongly evaluated as being inadmissible deviations.